Randomized k-server algorithms for growth-rate bounded graphs

The k-server problem is a fundamental online problem where k mobile servers should be scheduled to answer a sequence of requests for points in a metric space as to minimize the total movement cost. While the deterministic competitive ratio is at least k, randomized k-server algorithms have the potential of reaching o(k)-competitive ratios. Prior to this work only few specific cases of this problem were solved. For arbitrary metric spaces, this goal may be approached by using probabilistic metric approximation techniques. This paper gives the first results in this direction, obtaining o(k)-competitive ratio for a natural class of metric spaces, including d-dimensional grids, and wide range of k.     

The k-Client Problem

Virtually all previous research in online algorithms has focused on single-threaded systems where only a single sequence of requests compete for system resources. To model multithreaded online systems, we define and analyze the k-client problem, a dual of the well-studied k-server problem. In the basic k-client problem, there is a single server and k clients, each of which generates a sequence of requests for service in a metric space. The crux of the problem is deciding which client's request the single server should service rather than which server should be used to service the current request. We also consider variations where requests have nonzero processing times and where there are multiple servers as well as multiple clients.We evaluate the performance of algorithms using several cost functions including maximum completion time and average completion time. Two of the main results we derive are tight bounds on the performance of several commonly studied disk scheduling algorithms and lower bounds of on the competitive ratio of any online algorithm for the maximum completion time and average completion time cost functions when k is a power of 2. Most of our results are essentially identical for the maximum completion time and average completion time cost functions.     

The Distributedk-Server Problem—A Competitive Distributed Translator fork-Server Algorithms

We consider thek-server problem23in a distributed setting. Given a network ofnprocessors andkidentical mobile servers, requests for service appear at the processors and a server must reach the request point. In addition to modeling problems in computer networks wherekidentical mobile resources are shared by the processors of the network, this models a realistic situation where the transfer of information is costly and there is no central control that governs the behavior of servers that move around to satisfy requests for service. We give a general translator to transform any deterministic global-control competitivek-server algorithm into a distributed competitive one. As consequences we get poly(k)-competitive distributed algorithms for the line, trees, and the ring. In contrast to the global-control case where there arek-server algorithms with competitive ratio that depends solely onk, we have a lower bound of Ω(max{k, (1/D) ·(log n/log log n)}) on the competitive ratio of any distributedk-server algorithm, where 1/Dis the ratio between the cost to transmit a message and the cost to move a server over the same distance. We also give a distributed version of the Harmonic randomizedk-server algorithm.     

k-Best Solutions under Distance Constraints in Valuated -Matroids

In discrete maximization problems one usually wants to find an optimal solution. However, in several topics like “alignments,” “automatic speech recognition,” and “computer chess” people are interested to find thekbest solutions for somek ≥ 2. We demand that theksolutions obey certain distance constraints to avoid that thekalternatives are too similar. Several results for valuated -matroids are presented, some of them concerning time complexity of algorithms.     

On-line k-Truck Problem and Its Competitive Algorithms

In this paper, based on the Position Maintaining Strategy (PMS for short), on-line scheduling of k-truck problem, which is a generalization of the famous k-server problem, is originally presented by our team. We proposed several competitive algorithms applicable under different conditions for solving the on-line k-truck problem. First, a competitive algorithm with competitive ratio 2k+1/ is given for any 1. Following that, if (c+1)/(c-1) holds, then there must exist a (2k-1)-competitive algorithm for k-truck problem, where c is the competitive ratio of the on-line algorithm about the relevant k-server problem. And then a greedy algorithm with competitive ratio 1+/, where lambda is a parameter related to the structure property of a given graph, is given. Finally, competitive algorithms with ratios 1+1/ are given for two special families of graphs.     

Searching for a subset of counterfeit coins: Randomization vs determinism and adaptiveness vs non‐adaptiveness

We are given n coins of which k are heavy (defective), while the remaining n ‐ k are light (good). We know both the weight of the good coins and the weight of the defective ones. Therefore, if we weigh a subset Q ? S with a spring scale, then the outcome will tell us exactly the number of defectives contained in Q. The problem, known as Counterfeit Coins problem, is to identify the set of defective coins by minimizing the number of weighings, also called queries. It is well known that Θ(klog _{k +1}(n/k)) queries are enough, even for non‐adaptive algorithms, in case k ≤ cn for some constant 0 < c < 1. A natural interesting generalization arises when we are required to identify any subset of m ≤ k defectives. We show that while for randomized algorithms \begin{align*}\tilde{\Theta}(m)\end{align*} queries are sufficient, the deterministic non‐adaptive counterpart still requires Θ(klog _{k +1}(n/k)) queries, in case k ≤ n/2⁸; therefore, finding any subset of defectives is not easier than finding all of them by a non‐adaptive deterministic algorithm. © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2012     

Dense trees: a new look at degenerate graphs

Dense trees are undirected graphs defined as natural extensions of trees. They are already known in the realm of graph coloring under the name of k-degenerate graphs. For a given integer k1, a k-dense cycle is a connected graph, where the degree of each vertex is greater than k. A k-dense forest F=(V,E) is a graph without k-dense cycles as subgraphs. If F is connected, then is a k-dense tree. 1-dense trees are standard trees. We have |E|k|V|−k(k+1)/2. If equality holds F is connected and is called a maximal k-dense tree. k-trees (a subfamily of triangulated graphs) are special cases of maximal k-dense trees.We review the basic theory of dense trees in the family of graphs and show their relation with k-trees. Vertex and edge connectivity is thoroughly investigated, and the role of maximal k-dense trees as “reinforced” spanning trees of arbitrary graphs is presented. Then it is shown how a k-dense forest or tree can be decomposed into a set of standard spanning trees connected through a common “root” of k vertices. All sections include efficient construction algorithms. Applications of k-dense trees in the fields of distributed systems and data structures are finally indicated.     

An Efficient Algorithm for a Sparse k-Edge-Connectivity Certificate

We present an efficient algorithm for finding a sparse k-edge-connectivity certificate of a multigraph G. Our algorithm runs in O((log kn)(log k)²(log n)²) time using O(k(n + m′)) processors on an ARBITRARY CRCW PRAM, where n and m′ stand for the numbers of vertices in G and edges in the simplified graph of G, respectively.     

A general framework of compactly supported splines and wavelets

Let {V_k} be a nested sequence of closed subspaces that constitute a multiresolution analysis of L²( ). We characterize the family Φ = {φ} where each φ generates this multiresolution analysis such that the two-scale relation of φ is governed by a finite sequence. In particular, we identify the ε Φ that has minimum support. We also characterize the collection Ψ of functions η such that each η generates the orthogonal complementary subspaces W_k of V_k, . In particular, the minimally supported ψ ε Ψ is determined. Hence, the “B-spline” and “B-wavelet” pair (, ψ) provides the most economical and computational efficient “spline” representations and “wavelet” decompositions of L² functions from the “spline” spaces V_k and “wavelet” spaces W_k, k . A very general duality principle, which yields the dual bases of both {(·−j):j and {η(·−j):j } for any η ε Ψ by essentially interchanging the pair of two-scale sequences with the pair of decomposition sequences, is also established. For many filtering applications, it is very important to select a multiresolution for which both and ψ have linear phases. Hence, “non-symmetric” and ψ, such as the compactly supported orthogonal ones introduced by Daubechies, are sometimes undesirable for these applications. Conditions on linear-phase φ and ψ are established in this paper. In particular, even-order polynomial B-splines and B-wavelets φ_m and ψ_m have linear phases, but the odd-order B-wavelet only has generalized linear phases.     

Orlicz capacities and Hausdorff measures on metric spaces

In the setting of doubling metric measure spaces with a 1-Poincaré inequality, we show that sets of Orlicz Φ-capacity zero have generalized Hausdorff h-measure zero provided thatwhere Θ⁻¹ is the inverse of the function Θ(t)=Φ(t)/t, and s is the “upper dimension” of the metric measure space. This condition is a generalization of a well known condition in Rⁿ. For spaces satisfying the weaker q-Poincaré inequality, we obtain a similar but slightly more restrictive condition. Several examples are also provided.     

Where does smoothness count the most for Fredholm equations of the second kind with noisy information?

We study the complexity of Fredholm problems (I−T_k)u=f of the second kind on I^d=[0,1]^d, where T_k is an integral operator with kernel k. Previous work on the complexity of this problem has assumed either that we had complete information about k or that k and f had the same smoothness. In addition, most of this work has assumed that the information about k and f was exact. In this paper, we assume that k and f have different smoothness; more precisely, we assume that fW^r,p(I^d) with r>d/p and that kW^s,∞(I^2d) with s>0. In addition, we assume that our information about k and f is contaminated by noise. We find that the nth minimal error is Θ(n^−μ+δ), where μ=min{r/d,s/(2d)} and δ is a bound on the noise. We prove that a noisy modified finite element method has nearly minimal error. This algorithm can be efficiently implemented using multigrid techniques. We thus find tight bounds on the -complexity for this problem. These bounds depend on the cost c(δ) of calculating a δ-noisy information value. As an example, if the cost of a δ-noisy evaluation is proportional to δ^−t, then the -complexity is roughly (1/)^t+1/μ.     

Faster algorithms for string matching with k mismatches

The string matching with mismatches problem is that of finding the number of mismatches between a pattern P of length m and every length m substring of the text T. Currently, the fastest algorithms for this problem are the following. The Galil–Giancarlo algorithm finds all locations where the pattern has at most k errors (where k is part of the input) in time O(nk). The Abrahamson algorithm finds the number of mismatches at every location in time . We present an algorithm that is faster than both. Our algorithm finds all locations where the pattern has at most k errors in time . We also show an algorithm that solves the above problem in time O((n+(nk³)/m)logk).     

Dynamic Coresets

We give a dynamic data structure that can maintain an ε-coreset of n points, with respect to the extent measure, in O(log n) time per update for any constant ε>0 and any constant dimension. The previous method by Agarwal, Har-Peled, and Varadarajan requires polylogarithmic update time. For points with integer coordinates bounded by U, we alternatively get O(log log U) time. Numerous applications follow, for example, on dynamically approximating the width, smallest enclosing cylinder, minimum bounding box, or minimum-width annulus. We can also use the same approach to maintain approximate k-centers in time O(log n) (or O(log log U) if the spread is bounded by U) for any constant k and any constant dimension. For the smallest enclosing cylinder problem, we also show that a constant-factor approximation can be maintained in O(1) randomized amortized time on the word RAM. This work has been supported by NSERC. A preliminary version of this paper has appeared in Proc. 24th ACM Sympos Comput. Geom., 2008.     

Traversing Layered Graphs Using the Work Function Algorithm

The work function algorithm (WFA) is an on-line algorithm that has been studied mostly in connection with thek-server problem, but can actually be used on a wide variety of on-line problems. Despite being a simple algorithm, WFA has proven to be difficult to analyze, and until recently few interesting results were known. We analyze the performance of the generalized work function algorithm, denoted α-WFA, for on-line traversal of layered graphs. We show that for layered graphs of widthkand any α>1, α-WFA achieves competitive ratio (α+1)(2α/(α−1))^k−1−α. This gives anO(k2^k)-competitive ratio for appropriate choice of α, improving the previous upper bound ofO(k³2^k).     

On shredders and vertex connectivity augmentation

We consider the following problem: given a k-(node) connected graph G find a smallest set F of new edges so that the graph G+F is (k+1)-connected. The complexity status of this problem is an open question. The problem admits a 2-approximation algorithm. Another algorithm due to Jordán computes an augmenting edge set with at most (k−1)/2 edges over the optimum. CV(G) is a k-separator (k-shredder) of G if |C|=k and the number b(C) of connected components of G−C is at least two (at least three). We will show that the problem is polynomially solvable for graphs that have a k-separator C with b(C)k+1. This leads to a new splitting-off theorem for node connectivity. We also prove that in a k-connected graph G on n nodes the number of k-shredders with at least p components (p3) is less than 2n/(2p−3), and that this bound is asymptotically tight.     

A New Way of Using Semidefinite Programming with Applications to Linear Equations mod p

We introduce a new method of constructing approximation algorithms for combinatorial optimization problems using semidefinite programming. It consists of expressing each combinatorial object in the original problem as a constellation of vectors in the semidefinite program. When we apply this technique to systems of linear equations mod p with at most two variables in each equation, we can show that the problem is approximable within (1 − κ(p))p, where κ(p) > 0 for all p. Using standard techniques, we also show that it is NP-hard to approximate the problem within a constant ratio, independent of p.     

Induced disjoint paths problem in a planar digraph

As an extension of the disjoint paths problem, we introduce a new problem which we call the induced disjoint paths problem. In this problem we are given a graph G and a collection of vertex pairs {(s₁,t₁),…,(s_k,t_k)}. The objective is to find k paths P₁,…,P_k such that P_i is a path from s_i to t_i and P_i and P_j have neither common vertices nor adjacent vertices for any distinct i,j.The induced disjoint paths problem has several variants depending on whether k is a fixed constant or a part of the input, whether the graph is directed or undirected, and whether the graph is planar or not. We investigate the computational complexity of several variants of the induced disjoint paths problem. We show that the induced disjoint paths problem is (i) solvable in polynomial time when k is fixed and G is a directed (or undirected) planar graph, (ii) NP-hard when k=2 and G is an acyclic directed graph, (iii) NP-hard when k=2 and G is an undirected general graph.As an application of our first result, we show that we can find in polynomial time certain structures called a “hole” and a “theta” in a planar graph.     

Faster Subtree Isomorphism

We study the subtree isomorphism problem: Given trees H and G, find a subtree of G which is isomorphic to H or decide that there is no such subtree. We give an O((k^1.5/log k)n)-time algorithm for this problem, where k and n are the number of vertices in H and G, respectively. This improves over the O(k^1.5n) algorithms of Chung and Matula. We also give a randomized (Las Vegas) O(k^1.376n)-time algorithm for the decision problem.     

Twisted loop groups and their affine flag varieties

We develop a theory of affine flag varieties and of their Schubert varieties for reductive groups over a Laurent power series local field k((t)) with k a perfect field. This can be viewed as a generalization of the theory of affine flag varieties for loop groups to a “twisted case”; a consequence of our results is that our construction also includes the flag varieties for Kac–Moody Lie algebras of affine type. We also give a coherence conjecture on the dimensions of the spaces of global sections of the natural ample line bundles on the partial flag varieties attached to a fixed group over k((t)) and some applications to local models of Shimura varieties.     

Efficient offline algorithms for the bicriteria k-server problem and online applications

In this paper we consider the bicriteria version of the well-known k-server problem in which the cost incurred by an algorithm is evaluated simultaneously with respect to two different edge weightings.We show that it is possible to achieve the same competitive ratios of the previously known online algorithms with a dramatic improvement of the running time, i.e., from exponential to polynomial.Such results are obtained by exploiting new polynomial time algorithms able to find offline solutions whose costs differ from the optimal ones only of additive terms independent from the sequence of requests.